A Systematic Review of Resident Aesthetic Clinic Outcomes
Bibliographic record
Abstract
BACKGROUND: Providing residents with comprehensive training in aesthetic surgery has proven challenging. Resident aesthetic clinics propose an educational value to trainees while providing successful patient outcomes. OBJECTIVES: This study systematically reviewed the available literature regarding resident aesthetic clinic outcomes to determine the efficacy of the clinic in resident training, surgical results, and patient satisfaction. METHODS: An electronic database search was performed to identify literature reporting on resident aesthetic clinics. Studies were excluded if the resident clinic was not aesthetic in nature, if only nonsurgical aesthetic procedures were performed, and if clinic outcomes were not evaluated. Study quality was assessed using the Newcastle Ottawa Scale for nonrandomized studies. RESULTS: Ten of 148 identified studies met inclusion criteria; 2 utilized a survey, 3 were retrospective cohort studies, and 5 were retrospective cohort studies also utilizing a survey. Clinic schedules, surgical case volume, and surgical procedures performed all varied. One study received a Newcastle Ottawa Scale score of 7 of a possible 9 stars, 2 studies received 5 stars, 5 studies received 4 stars, and 2 could not be assessed using the scoring system. Six studies analyzed surgical results as a primary outcome, reporting acceptable complication and revision rates. Four studies evaluated patient opinions of the clinics and reported overall high satisfaction rates. CONCLUSIONS: This systematic review suggests that resident aesthetic clinics enhance resident education while providing safe and successful surgical results to patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".